SciPredict: Can LLMs Predict the Outcomes of Scientific Experiments in Natural Sciences?
Accelerating scientific discovery requires the identification of which experiments would yield the best outcomes before committing resources to costly physical validation. While existing benchmarks evaluate LLMs on scientific knowledge and reasoning, their ability to predict experimental outcomes - a task where AI could significantly exceed human capabilities - remains largely underexplored. We introduce SciPredict, a benchmark comprising 405 tasks derived from recent empirical studies in 33 specialized sub-fields of physics, biology, and chemistry. SciPredict addresses two critical questions: (a) can LLMs predict the outcome of scientific experiments with sufficient accuracy? and (b) can...
| Authors | Udari Madhushani Sehwag, Elaine Lau, Haniyeh Ehsani Oskouie et al. |
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| Primary category | cs.AI |
| Published | 12 April 2026 |
| Last updated at source | 12 April 2026 |
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